CN108601820A - Compositions and methods for viral cancer neo-epitopes - Google Patents

Abstract

the present invention provides methods and compositions for making and using recombinant viruses or other recombinant expression systems in which neoepitopes are first identified in a patient-specific and cancer-specific manner, then further filtered by matching with the patient's H L A.

Description

Compositions and methods for viral cancer neo-epitopes

This application claims priority to US Provisional Application Serial No. 62/240487, filed October 12, 2015.

technical field

The field of the invention is genetically modified viruses as therapeutic modalities for the treatment of cancer, and in particular the field relates to viral delivery and expression of patient-specific HLA-matched neo-epitopes.

Background technique

The Background Description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication cited, either expressly or impliedly, is prior art.

All publications and patent applications herein are herein incorporated by reference as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. When a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in that reference does not apply.

Recently, immunotherapy using genetically modified viruses has emerged as a conceptually valid and attractive avenue for the treatment of various cancers. However, many challenges remain to be resolved. For example, the choice of a suitable antigen to be expressed is of interest (see eg Nat Biotechnol. 2012 Jul 10;30(7):658-70). Furthermore, even frequently expressed epitopes do not guarantee a strong tumor-protective immune response in all patients. In addition, patients will also develop an immune response to most viral vectors, thus precluding the use of viruses in previously exposed patients and limiting vectors to single use. Among other viruses, adenoviruses are commonly used in gene therapy (see eg Oncotarget. 2015 Aug 21;6(24):19976-89), but similar disadvantages still exist.

In order to reduce immunogenicity, genetically modified adenoviruses have been reported which are suitable not only for multiple vaccinations but also for vaccination of individuals with pre-existing immunity to adenoviruses (see for example WO 2009/006479 and WO 2014/ 031178), usually by deleting the E2b gene and other late proteins to reduce immunogenicity. Moreover, due to these specific deletions, such genetically modified viruses are replication defective and allow relatively large recombinant cargoes. For example WO 2014/031178 describes the use of such genetically modified viruses to express CEA (colorectal embryonic antigen) to provide an immune response against colon cancer. Although at least some outcome measures improved in the treatment group with this virus, various shortcomings persist. Among other factors, a single expressed antigen common to many tumors may not be sufficient to mount a meaningful immune response. Furthermore, because the immune system varies significantly from patient to patient, the predictability and efficacy of individual antigens is often not apparent.

Thus, even though various systems and methods for immunotherapy of various cancers are known in the art, all or nearly all of them suffer from several disadvantages. Most notably, given the relatively high number of neoepitopes in many cancers, parameters that predict immunogenicity of neoepitopes remain elusive. Thus, currently known systems and methods do not provide a rational design approach for neoepitope-based immunotherapy. Therefore, there remains a need for improved systems and methods for neoepitope selection and neoepitope-based therapy

Contents of the invention

The subject of the present invention relates to systems, compositions and methods of immunotherapy in which a rational design approach is used to identify neo-epitopes with high specificity and reactivity for patients in which they are identified. This high-confidence neo-epitope is then delivered, preferably via a genetically engineered replication-defective non-immunogenic virus (i.e., that does not elicit protective immunity of the virus in the host upon exposure to the virus) or otherwise expressed The system stimulates an immune response in this way.

In one aspect of the inventive subject matter, the inventors contemplate a method of treating cancer in a patient using immunotherapy comprising the step of producing a recombinant nucleic acid configured to express cancer-specific and patient-specific neo-epitopes. Most typically, the neo-epitope is a high affinity binder of at least one MHC class I subtype or at least one MHC class II subtype of the patient's HLA class. Furthermore, it is contemplated that the recombinant nucleic acid in such methods comprises sequence elements that direct the presentation of expressed neo-epitopes to at least one MHC class I subtype or at least one MHC class II subtype. In a further step, the cells are transfected with recombinant nucleic acids (e.g. using viruses, viral expression vectors, bacterial expression vectors, yeast expression vectors or RNA) to thereby force the cells to express and express on at least one MHC class I subtype of the cells or presentation of cancer-specific and patient-specific neo-epitopes on at least one MHC class II subtype, wherein the transfection step is performed in the patient or wherein the transfected cells are administered to the patient.

Further general consideration is given to the identification of cancer-specific and patient-specific neo-epitopes by comparing omics data of diseased and healthy tissues of patients, and/or by identifying mutation types, transcriptional strengths, translational strengths, and previously known molecular At least one of the variants is filtered to identify cancer-specific and patient-specific neoepitopes. Most typically, high affinity binders have an affinity of less than 150 nM for at least one MHC class I subtype or at least one MHC class II subtype, and/or computer determination of the patient's HLA class using de Bruijn diagrams.

In a further aspect of such methods, the sequence element is a lysosomal targeting sequence, an endosomal targeting sequence, a peroxisome targeting sequence, or a cytoplasmic retention sequence, and the recombinant nucleic acid may further comprise a sequence encoding a co-stimulatory molecule and/or sequences encoding checkpoint inhibitors.

Although not limited to the subject matter of the present invention, the cells are typically immunocompetent or antigen-presenting cells of the patient, and adenovirus can be used to achieve transfection in the patient. Furthermore, it is contemplated that such methods may include the additional validation of neo-epitopes by at least one MHC class I subtype or by at least one Steps in the presentation of an MHC class II subtype. Alternatively, the contemplated method further comprises the step of verifying presentation of the neo-epitope by at least one MHC class I subtype or by at least one MHC class II subtype in cancer cells of the patient or cancerous tissue of the patient. For example, such a verification step may use a synthetic conjugate or antibody that binds a neo-epitope to perform a step of verifying presentation.

In another aspect of the inventive subject matter, the inventors contemplate a method of producing recombinant nucleic acids for use in immunotherapy comprising comparing omics data of diseased and healthy tissues of a patient to identify disease-associated patient-specific novel Epitope steps. In a further step, at least one MHC class I subtype and at least one MHC class II subtype of the patient's HLA class are identified, and the association of neo-epitopes with at least one MHC class I subtype and at least one MHC class II subtype is determined. Binding affinity of MHC subtypes. This neo-epitope is then selected for further use when the binding affinity is below a predetermined threshold. In a further step of such methods, a recombinant nucleic acid (e.g., an adenoviral expression vector) is constructed to include a nucleic acid sequence encoding the selected neo-epitope, wherein the nucleic acid sequence encoding the selected neo-epitope is responsible for driving the selected neo-epitope. The expression of the epitope is under the control of the promoter. Most typically, the nucleic acid sequence further comprises a sequence element that directs presentation of the expressed neo-epitope to at least one MHC class I subtype or at least one MHC class II subtype.

It is generally contemplated that in such a method, the step of comparing omics data is performed by incremental simultaneous alignment of omics data, and/or using de Bruijn graph computer to determine at least one MHC class I subtype and at least one Class II MHC subtypes. Furthermore, computer determination of the binding affinity of the neo-epitope to at least one MHC class I subtype and at least one MHC class II subtype is contemplated, wherein the predetermined threshold is less than 150 nM.

It is further generally contemplated that the recombinant nucleic acid may further comprise a second nucleic acid sequence encoding a second neoepitope, and/or a sequence encoding a co-stimulatory molecule and/or a sequence encoding a checkpoint inhibitor. Suitable sequence elements include lysosomal targeting sequences, endosomal targeting sequences, peroxisome targeting sequences and/or cytoplasmic retention sequences.

Therefore, the present inventors also contemplated a method of improving cancer neoantigen presentation, which is a step of comparing omics data of diseased and healthy tissues of a patient to identify multiple disease-associated patient-specific neoepitopes of the patient. In a further step, filtered neo-epitopes are obtained by filtering disease-associated patient-specific neo-epitopes by at least one of mutation type, transcriptional intensity, translational intensity, and/or a priori known molecular variation. In a further step, high-affinity binders of at least one MHC class I subtype or at least one MHC class II subtype of the patient's HLA class are selected from the filtered neo-epitopes and are present in the patient's cells or with compatible HLA The high-affinity binder is expressed in cells of this type. In a further step, presentation of the high affinity binder by at least one MHC class I subtype or by at least one MHC class II subtype is verified, and after verification of expression and presentation, the high affinity binder is used in an immunotherapy format conjugates.

Most preferably, the step of comparing the omics data is performed by incremental simultaneous comparison of the omics data, and wherein the diseased tissue is cancerous tissue. In further contemplated aspects, the mutation type is a missense mutation, wherein transcriptional intensity is measured by RNAseq, wherein translational intensity is measured by selective reaction monitoring mass spectrometry, and wherein the previously known molecular variation includes single nucleotide polymorphisms, short At least one of deletion and insertion polymorphisms, microsatellite markers, short tandem repeats, heterozygous sequences, polynucleotide polymorphisms, and named variants. Furthermore, high affinity binders having an affinity of less than 150 nM for at least one MHC class I subtype or at least one MHC class II subtype are also contemplated. Additionally, it is contemplated that in such methods, the patient's cells or cells of a compatible HLA type are antigen-presenting cells (e.g., dendritic cells, natural killer cells, macrophages, T cells), and/or have a compatible HLA type of cells have the same tissue type as the diseased tissue.

The step of verifying the presentation of the high affinity binder uses a step of detecting the binding of the high affinity binder on the surface of the patient's cells or cells of a compatible HLA type (e.g. by a synthetic binder or antibody that binds the high affinity binder). In yet another contemplated aspect, the immunotherapy modality is a recombinant adenovirus, viral expression vector, bacterial expression vector, yeast expression vector, or RNA.

In yet another aspect of the inventive subject matter, the inventors contemplate a method of improving cancer neoantigen presentation in which omics data of a patient's diseased and healthy tissue are compared in one step to identify multiple disease-associated patient-specific Sexual neoepitopes. In another step, the filtered neo-epitopes are obtained by filtering disease-associated patient-specific neo-epitopes by at least one of mutation type, transcriptional intensity, translational intensity, and molecular variation known in advance, and from the filtered neo-epitopes The epitope selects high affinity binders of at least one MHC class I subtype or at least one MHC class II subtype of the patient's HLA class. In a further step, a synthetic conjugate that specifically binds the high affinity binder is prepared, and the synthetic conjugate is detected for binding to cells or tissues of the patient. After validating the binding of the synthetic peptides, this high affinity binder was used in an immunotherapy format.

Most preferably, the step of comparing the omics data is performed by incremental simultaneous comparison of the omics data, and wherein the diseased tissue is cancerous tissue. In further contemplated aspects, the mutation type is a missense mutation, wherein transcriptional intensity is measured by RNAseq, wherein translational intensity is measured by selective reaction monitoring mass spectrometry, and wherein the previously known molecular variation includes single nucleotide polymorphisms, short At least one of deletion and insertion polymorphisms, microsatellite markers, short tandem repeats, heterozygous sequences, polynucleotide polymorphisms, and named variants. Furthermore, high affinity binders having an affinity of less than 150 nM for at least one MHC class I subtype or at least one MHC class II subtype are also contemplated.

Synthetic conjugates are preferably antibodies or fragments thereof, or peptides obtained from phage display or RNA display. Furthermore, for detection steps, it is contemplated that such steps will include optical detection of synthetic conjugates on patient cells or tissue (eg, where patient cells or tissue are placed in a biopsy sample). As previously noted, suitable immunotherapy formats thereof include recombinant adenoviruses, viral expression vectors, bacterial expression vectors, yeast expression vectors or RNA.

Thus, and from a different perspective, the inventors also contemplate recombinant viruses comprising nucleic acids produced by the methods contemplated by the present invention. Such viruses (or other expression systems) can then be included in pharmaceutical compositions for the treatment of cancer.

Various objects, features, aspects and advantages of the inventive subject matter will become more apparent from the following detailed description of the preferred embodiments.

Description of drawings

1A and 1B are exemplary schematic diagrams of the localization of HLA types on human chromosomes, allelic diversity (FIG. 1A) and expression and membrane localization (FIG. 1B).

Figure 2 is an exemplary graph depicting the filtering results of calculated neo-epitopes.

Detailed ways

The present inventors have now discovered various systems, compositions and methods of immunotherapy in which viral vectors or other expression systems are used to deliver one or more patient-specific and cancer-specific antigens to a host for therapeutic effect. Most typically, the therapeutic effect is a protective immune response against cells or pathogens bearing the antigen. Accordingly, and in one particularly contemplated aspect of the inventive subject matter, it is preferred to use nucleic acid sequence information from a patient's tumor and matched normal (i.e., non-cancerous) tissue samples to determine the patient-specific and specificity of an individual diagnosed with cancer. Cancer-specific neoepitopes. In this context, it should be understood that in cases where tumor and matched normal samples are used to identify neoepitopes, all or nearly all otherwise observed non-tumor associations between the patient sample and the reference genome are excluded Variety. Thus, from a different perspective, comparisons between tumors of the same patient and matched normal samples will eliminate all inter-individual or patient-to-reference variation that occurs at a higher frequency, and thus will eliminate a large number of possible false positive new tables. bit.

Additionally, to increase the likelihood of proper presentation and recognition of patient-specific and cancer-specific neoepitopes so identified, the patient's specific HLA type is determined (e.g., using in silico prediction as described in more detail below) and the identified epitopes are tested in silico. The binding affinities of the neo-epitopes for the determined HLA types. Most typically, HLA typing includes at least three MHC-I subtypes (eg, HLA-A, HLA-B, HLA-C) and at least three MHC-II subtypes (eg, HLA-DP, HLA-DQ, HLA -DR), preferably wherein each subtype is determined to be at least 4 bits deep. The sequences of the high-affinity binders thus identified are then back-translated into their corresponding nucleic acid sequences, which are then cloned into a recombinant expression system for expression in host cells infected with viruses under the control of one or more regulatory sequences ( For example in adenovirus Ad5[E1-E2b-]). Still further, it will be appreciated that preferred expression systems will also include one or more sequence elements associated with the neoepitope sequence which will direct the expressed neoepitopes towards MHC-I and/or MHC-I for which they have high affinity MHC-II subtypes.

Thus, it is expected that recombinant viruses or other expression systems will result in the intracellular expression of true patient-specific and cancer-specific neo-epitopes that are not only adapted but also directed for presentation to HLA, which Presentation is established with high affinity for neo-epitopes, which in turn are expected to generate highly predictable immune responses, leading to therapeutically effective immune responses against tumors in the host.

To further increase the chances of a therapeutically effective immune response against the tumor, expression and presentation of neo-epitopes can be tested in various ways, as further discussed in more detail below. After satisfactory testing in vitro, the neo-epitope can be used as a therapeutic agent in vivo, typically by expression in cells in the patient. Of course, it should be noted that multiple neo-epitopes may be used in conjunction with the teachings presented herein, and in particularly preferred aspects at least two, at least three, at least four or at least five different neo-epitopes will be used. Epitopes (eg, encoded in the same recombinant virus, or encoded in different viruses). Finally, the expression system may further include additional sequences encoding proteins that support an immune response within the context of the cell expressing the neo-epitope. For example, suitable proteins include immunostimulatory cytokines (such as IL-2, IL-7, IL-12, IL-15 or IL-15 superagonists, etc.), checkpoint inhibitors (such as CTLA-4 inhibitors or PD1 signaling) and/or co-stimulatory molecules (such as CD80, CD86, etc.).

Selection of neoepitopes

Neoepitopes can be characterized as random mutations expressed in tumor cells that produce unique tumor-specific antigens. Thus, from a different perspective, neo-epitopes can be identified by considering the type of mutation (e.g. deletion, insertion, transversion, transition, translocation) and effect (e.g. nonsense, missense, frameshift, etc.), which This can thus serve as a first content filter by which silent and other irrelevant (eg non-expressing) mutations are eliminated. It should further be understood that a neo-epitope sequence may be defined as a sequence stretch of relatively short length (eg, a 7-11 mer), wherein such a stretch would include changes in the amino acid sequence. Most typically, the altered amino acid will be at or near the central amino acid position. For example, a typical neo-epitope may have the structure A ₄ -NA ₄ , or A ₃ -NA ₅ , or A ₂ -NA ₇ , or A ₅ -NA ₃ , or A ₇ -NA ₂ , where A is a proteinogenic amino acid Whereas N is the altered amino acid (relative to wild type or relative to matched normal). For example, neo-epitope sequences contemplated herein include sequence extensions of relatively short length (e.g., 5-30mers, more typically 7-11mers or 12-25mers), where such extensions would include Changes in Amino Acid Sequence.

Thus, it will be appreciated that, depending on the position of the altered amino acid, a single amino acid change may be presented in many neo-epitope sequences comprising the altered amino acid. Advantageously, such sequence variability allows many choices of neo-epitopes, and thus increases the number of potentially useful targets, which can then be based on one or more desired traits (e.g. highest affinity for the patient's HLA type, highest structural stability, etc.) to select potentially useful targets. Most typically, neo-epitopes will be calculated to be 2-50 amino acids, more typically 5-30 amino acids, most typically 9-15 amino acids in length, with the altered amino acids preferably centrally or otherwise located Improve the way it binds to MHC. For example, in the case of an epitope presented by the MHC-I complex, a typical neo-epitope would be about 8-11 amino acids in length, while a typical neo-epitope for presentation via the MHC-II complex would be about 8-11 amino acids in length. The length is about 13-17 amino acids. As will be readily appreciated, since the position of the altered amino acids in a neo-epitope may not be central, the actual peptide sequence as well as the actual topology of the neo-epitope may vary significantly.

Of course, it should be recognized that the identification or discovery of neoepitopes can start from a variety of biological materials, including fresh biopsies, frozen or otherwise preserved tissue or cell samples, circulating tumor cells, exosomes, various bodily fluids ( especially blood) etc. Therefore, suitable omics analysis methods include nucleic acid sequencing, especially NGS methods that operate on DNA (such as Illumina sequencing, ion torrent sequencing, 454 pyrosequencing, nanopore sequencing, etc.), RNA sequencing (such as RNAseq , reverse transcription-based sequencing, etc.) and protein sequencing or mass spectrometry-based sequencing (eg, SRM, MRM, CRM, etc.).

Therefore, particularly for nucleic acid-based sequencing, it should be particularly recognized that high-throughput genomic sequencing of tumor tissue will allow rapid identification of neo-epitopes. However, it must be recognized that normally occurring patient-to-patient variation (eg, due to SNPs, short indels, varying numbers of repeats, etc.) as well as heterozygosity will result in a considerable potential False positive neo-epitopes. Therefore, many of the neo-epitopes identified will be unlikely candidates for successful immunization strategies. Remarkably, this inaccuracy can be removed when comparing a patient's tumor sample to a matched normal (i.e., non-tumor) sample from the same patient.

In a particularly preferred aspect of the inventive subject matter, DNA analysis is performed by whole genome sequencing and/or exome sequencing (typically at a depth of coverage of at least 10x, more typically at least 20x) of both tumor and matched normal samples. Alternatively, DNA data can also be provided from established sequence records (eg, SAM, BAM, FASTA, FASTQ or VCF files) from previous sequence determinations. Thus, data sets may include unprocessed or processed data sets, and exemplary data sets include data sets in BAMBAM format, SAMBAM format, FASTQ format, or FASTA format. However, it is particularly preferred that the dataset is provided in BAMBAM format or as a BAMBAM diff object (see eg US2012/0059670A1 and US2012/0066001A1). Additionally, it should be noted that the datasets reflect tumors and matched normal samples from the same patient to obtain patient and tumor specific information. Thus, genetic germline changes (eg, silent mutations, SNPs, etc.) that are not tumor-causing can be ruled out. Of course, it should be appreciated that the tumor sample can be from the original tumor, from the tumor at the start of treatment, from a recurrent tumor or metastatic site, and the like. In most cases, a patient's matched normal sample can be blood or non-diseased tissue from the same tissue type as the tumor.

Similarly, computational analysis of sequence data can be performed in a number of ways. However, in the most preferred method, the analysis is performed in silico by position-guided simultaneous alignment of tumor and normal samples using BAM files and BAM servers, for example as disclosed in US 2012/0059670A1 and US 2012/0066001A1 . Such analysis advantageously reduces false positive neo-epitopes and significantly reduces memory and computing resource requirements.

It should be noted that any computer-directed language should be understood to include any appropriate combination of computing devices, including servers, interfaces, systems, databases, agents, peers, engines, controllers, or other types of operating alone or collectively computing equipment. It should be understood that a computing device includes a processor configured to execute software instructions stored on a tangible, non-transitory computer-readable storage medium (eg, hard drive, solid-state drive, RAM, flash memory, ROM, etc.). The software instructions preferably configure the computing device to provide roles, responsibilities or other functions as discussed below with respect to the disclosed apparatus. Furthermore, the disclosed technology may be embodied as a computer program product comprising a non-transitory computer-readable medium storing software instructions that cause a processor to execute computer-based algorithms, procedures, methods, or other instructions. In particularly preferred embodiments, the various servers, systems, databases or interfaces may use standardized protocols or algorithms based on HTTP, HTTPS, AES, public key exchange, web service APIs, known financial transaction protocols, or other electronic information exchange methods to exchange data. Data exchange between devices may be performed over a packet-switched network, the Internet, a LAN, WAN, VPN, or other types of packet-switched networks; circuit-switched networks; cell-switched networks; or other types of networks.

To further facilitate computational analysis and improve therapeutic outcomes based on neoepitope therapeutics, neoepitope sequences will be limited to relatively small fragments with the minimum size (e.g., at least 5-6 amino acids) necessary for MHC-I binding, and favor a maximum size for MHC-I binding (e.g. 9-11 amino acids), or be limited to relatively small fragments with the minimum size necessary for MHC-II binding (e.g. at least 12-14 amino acids) and favor MHC - Maximum size for II binding (eg 19-21 amino acids). Thus, for MHC-I binding, neo-epitopes are usually 7-12 amino acids in length, and for MHC-II binding, neo-epitopes are usually 14-20 amino acids in length. For example, suitable neo-epitopes may be 9 amino acids in length (where they are determined to bind MHC-I), including altered amino acids, and 20 amino acids in length (where they are determined to bind MHC-II). combination), including altered amino acids.

From a different point of view, patient-specific and cancer-specific collections of computer sequences having a predetermined length of 5 to 25 amino acids and including at least one altered amino acid can be built. Such sets typically comprise at least two, at least three, at least four, at least five, or at least six members for each altered amino acid, wherein the positions of the altered amino acids are not identical. Such collections can then be used for further filtering (eg, by subcellular localization, transcription/expression levels, MHC-I and/or II affinity, etc.) as described in more detail below.

For example, and using simultaneous localization-guided analysis of tumor and matched normal sequence data, the inventors previously identified various cancer neoepitopes from various cancers and patients, including the following cancer types: BLCA, BRCA, CESC, COAD , DLBC, GBM, HNSC, KICH, KIRC, KIRP, LAML, LGG, LIHC, LUAD, LUSC, OV, PRAD, READ, SARC, SKCM, STAD, THCA and UCEC. All neo-epitope data can be found in International Application PCT/US16/29244, which is incorporated herein by reference.

Depending on the type and stage of cancer, it should be noted that the number of neo-epitopes may far exceed the number actually available for immunotherapy. Moreover, not all neoepitopes so identified will necessarily result in a therapeutically effective response in patients. In fact, it is well known in the art that only a small fraction of neo-epitopes will generate an immune response. To increase the likelihood of a therapeutically desirable response, one can further filter for neo-epitopes. Of course, it should be understood that downstream analysis need not take into account silent mutations for the purposes of the methods presented herein. However, preferred mutation analysis provides information on the effect of the mutation (e.g. nonsense, missense, etc.) The first content filter for mutations. For example, when the mutation is a frameshift, nonsense and/or missense mutation, a neoepitope can be selected for further consideration.

In a further filtering approach, neo-epitopes can also be subjected to detailed analysis for subcellular localization parameters. For example, if a neo-epitope is identified as having a membrane-associated location (e.g., located on the outside of the cell membrane of the cell) and/or if in silico structural calculations confirm that the neo-epitope is likely to be solvent-exposed, or presents a structurally stable epitope (e.g., J Exp Med 2014) etc. can select neo-epitope sequences for further consideration.

As for filtering neo-epitopes, it is generally considered that neo-epitopes are particularly suitable for use herein where omics (or other) analysis shows that the neo-epitopes are actually expressed. The expression and identification of expression levels of neo-epitopes can be performed in all ways known in the art, and preferred methods include quantitative RNA (hnRNA or mRNA) analysis and/or quantitative proteomic analysis. Most typically, the threshold level for inclusion of a neo-epitope will be at least 20% of the expression level of the corresponding matched normal sequence, and more typically at least 50% of the expression level, thereby ensuring that the (neo) epitope is at least "likely" to the immune system. visible". Therefore, it is generally preferred that omics analysis also includes gene expression analysis (transcriptome analysis) in order to help identify the expression levels of genes with mutations.

A number of transcriptomic analysis methods are known in the art, and all known methods are considered suitable for use herein. For example, preferred ^{material includes mRNA and primary transcripts (hnRNA), and RNA sequence information can be obtained from reverse transcribed poly A + -RNA} , which in turn was obtained from tumor samples from the same patient and matched normal (healthy) samples were obtained. Also, it should be noted that while polyA ⁺ -RNA is generally preferred as a representative of the transcriptome, other RNA forms (hn-RNA, non-polyadenylated RNA, siRNA, miRNA, etc.) are also considered suitable for use herein. Preferred methods include quantitative RNA (hnRNA or mRNA) analysis and/or quantitative proteomic analysis, especially RNAseq. In other aspects, qPCR and/or rtPCR based methods are used for RNA quantification and sequencing, although various alternative methods such as solid phase hybridization based methods are also considered suitable. From another perspective, transcriptomic analysis may be suitable (alone or in combination with genomic analysis) to identify and quantify genes with cancer-specific and patient-specific mutations.

Similarly, proteomic analysis to determine the actual translation of RNA for neoepitopes can be performed in many ways, and all known ways of proteomic analysis are considered here. However, particularly preferred proteomic methods include antibody-based methods and mass spectrometry methods. In addition, it should be noted that proteomic analysis can not only provide qualitative or quantitative information about the protein itself, but also include protein activity data that the protein has catalytic or other functional activities. One exemplary technique for performing proteomic assays is described in US 7473532, which is incorporated herein by reference. Other suitable methods for identifying and even quantifying protein expression include various mass spectrometric analyzes (e.g. selective reaction monitoring (SRM), multiple reaction monitoring (MRM) and continuous reaction monitoring (CRM)) .

In yet another aspect of filtering, neo-epitopes can be compared against a database containing known human sequences (eg, sequences of a patient or collection of patients) to avoid using the same sequence for a human. In addition, filtering may also include removing neoepitopic sequences arising from SNPs in patients where the SNP is present in both tumor and matching normal sequences. For example, dbSNP (Database of Single Nucleotide Polymorphisms) is a free database of genetic variation within and across different species developed and hosted by the National Center for Biotechnology Information (NCBI) in collaboration with the National Human Genome Research Institute (NHGRI). public archives. Despite the name of the database containing a collection of only one class of polymorphisms (single nucleotide polymorphisms (SNPs)), it actually encompasses a relatively broad range of molecular variations: (1) SNPs, (2) short deletions and insertions Polymorphism (Indel/DIP), (3) microsatellite marker or short tandem repeat (STR), (4) polynucleotide polymorphism (MNP), (5) heterozygous sequence, and (6) nomenclature Variants. dbSNP accepts distinct neutral polymorphisms, polymorphisms corresponding to known phenotypes, and regions with no variation. Using such a database as described above and other filtering options, patient- and tumor-specific neo-epitopes can be filtered to remove those known sequences, yielding a sequence set of multiple neo-epitope sequences with significantly reduced false positives.

In less preferred aspects, cancer-specific and patient-specific neoepitopes can be augmented or even replaced with more common neoepitopes. For example, contemplated common neo-epitopes include various cancer-associated and cancer-specific antigens (eg, with a frequency of at least 0.1%, or at least 0.5%, or at least 1%, or at least 5%). Alternatively, suitable neoantigens may also include those identified as having a predetermined minimum frequency (e.g., a frequency of at least 0.1%, or at least 0.5%, or at least 1%, or at least 5%) in at least one particular MHC subtype Neoantigens present. Further aspects of neoepitopes, methods and systems related thereto are disclosed in our co-owned International Applications PCT/US16/26798 and PCT/US16/29244, both of which are incorporated herein by reference.

HLA determination and matching

The human major histocompatibility complex (MHC) or human leukocyte antigen (HLA) complex contains many genetic loci, including at least seven loci that encode coexpressed two distinct types of highly polymorphic cell surface antigens . These molecules bind and present processed peptides to circulating T-cell lymphocytes and are critical for both cellular and humoral immune responses. Thus, in the context of immunotherapy, it should therefore be evident that neo-epitopes are more likely to be effective when they are bound and presented by MHC complexes.

Unfortunately, however, the MHC complex is highly diverse and different in different patients, making neoepitope binding prediction difficult. The class I molecules HLA-A, HLA-B and HLA-C and the class II molecules DR, DQ and DP are encoded in an approximately 3500 kbp segment of the short arm of chromosome 6p21.31 (shown schematically in Figures 1A and 1B). Class I antigens are presented on all nucleated cells where they act as cell surface heterodimers that primarily present peptides from the cytosol (viral and self-peptides) to circulating CD8+ T cells. The class I cell surface heterodimer has a highly polymorphic alpha chain with variable residues clustered within the peptide-binding cleft encoded by exons 2 and 3 of the gene. HLA class I molecules also serve as ligands for the killer immunoglobulin receptor (KIR), which regulates the cytotoxic activity of natural killer (NK) cells. HLA class II molecules are found on the surface of B cells, macrophages and other antigen-presenting cells, where α-β heterodimers primarily present exogenously derived peptides (bacterial and chemical toxins) to circulating CD4+ T cells. In class II molecules, the β-strand contains a highly polymorphic region located in exon 2 of the gene and encoding a peptide-binding cleft.

Thus, it should be understood that efficient binding and presentation is a combined function of the patient's neoepitope sequence and specific HLA class. Most typically, HLA typing includes at least three MHC-I subtypes (eg, HLA-A, HLA-B, HLA-C) and at least three MHC-II subtypes (eg, HLA-DP, HLA-DQ, HLA -DR), preferably wherein each subtype is determined to be at least 4 bits deep. However, larger depths (eg 6-bit, 8-bit) are also considered in this paper.

Once the patient's HLA type has been determined (using known chemistry or in silico), the HLA type structure solution is calculated or obtained from a database, which is then used in a computer docking model to determine the (usually filtered) neoepitope pair HLA structure Binding affinity of the solution. As will be discussed further below, suitable systems for determining binding affinity include the NetMHC platform (see, eg, Nucleic Acids Res. 2008 Jul 1; 36 (Web Server issue): W509-W512.). Neo-epitopes with high affinity (eg less than 100 nM, less than 75 nM, less than 50 nM) for a predetermined HLA class are then selected together with knowledge of MHC-I/II subtypes for establishing therapy.

HLA determination can be performed using a variety of methods in wet chemistry well known in the art, and all of these methods are considered suitable for use herein. However, in a particularly preferred method, HLA types can also be predicted in silico from omics data using a reference sequence containing most or all known and/or common HLA types as shown in more detail below.

For example, in a preferred method according to the inventive subject matter, a relatively large number of patient sequences mapping to chromosome 6p21.3 (or near/at any other position where HLA alleles are found) are provided by databases or sequencing machines Read paragraph. The most typical sequence reads will be approximately 100-300 bases in length and contain metadata including read quality, alignment information, orientation, position, etc. For example, suitable formats include SAM, BAM, FASTA, GAR, and the like. While not limiting to the present subject matter, it is generally preferred that patient sequence reads provide at least 5-fold, more typically at least 10-fold, even more typically at least 20-fold, and most typically at least 30-fold depth of coverage.

In addition to patient sequence reads, the contemplated methods also use one or more reference sequences, which include the sequences of multiple known and different HLA alleles. For example, a typical reference sequence may be a synthetic (without a corresponding human or other mammalian counterpart) sequence comprising a sequence segment of at least one HLA-type with multiple HLA-alleles of that HLA type. For example, suitable reference sequences include the collection of known genomic sequences of at least 50 different alleles of HLA-A. Alternatively or additionally, the reference sequence may also comprise a collection of known RNA sequences of at least 50 different alleles of HLA-A. Of course, and as discussed further below in more detail, the reference sequence is not limited to the 50 alleles of HLA-A, but may have alternative compositions with respect to HLA type and number/composition of alleles. Most typically, the reference sequence will be in a computer readable format and will be available from a database or other data storage device. For example, suitable reference sequence formats include FASTA, FASTQ, EMBL, GCG, or GenBank formats, and can be obtained directly from public databases (e.g., IMGT, the International ImMunoGeneTics Information System or the Allele Frequency Network database, EUROSTAM, www.allelefrequencies.net). Get or build. Alternatively, a reference sequence can also be constructed from known HLA alleles of an individual based on one or more predetermined criteria, such as allele frequency, ethnic allele distribution, common or rare allele type, and the like.

Using the reference sequence, patient sequence reads can now be threaded through the de Bruijn diagram to identify the best-fitting allele. In this case, it should be noted that each individual carries two alleles of each HLA type, and these alleles may be very similar, or in some cases even identical. This high similarity is a major problem for traditional alignment schemes. The present inventors have now discovered that HLA alleles, and even very closely related alleles, can be resolved using a method of constructing de Bruijn plots by breaking sequence reads into relatively small k-mers (typically with 10 to 20 bases in length) and a de Bruijn graph was constructed by implementing a weighted voting process in which each patient sequence read was generated for each Alleles provide votes ("quantitative read support"). The allele with the highest cumulative vote indicates the most likely predicted HLA allele. Furthermore, it is generally preferred that each segment that matches an allele is also used to calculate the total coverage and depth of coverage for that allele.

The scores can be further increased or refined as desired, especially if many of the top hits are similar (eg, where a significant portion of their scores come from a highly shared set of k-mers). For example, scoring refinement may include a weighting scheme in which alleles that are substantially similar (eg, >99%, or other predetermined value) to the current top hit are removed from future consideration. The count of k-mers used by the current top hit is then reweighted by a factor (eg 0.5), and the score for each HLA allele is recalculated by summing these weighted counts. Repeat this selection process to find a new top hit. The accuracy of the method can be further improved using RNA sequence data that allows the identification of tumor expressed alleles, which may sometimes be only 1 of 2 alleles present in the DNA. In a further advantageous aspect of the contemplated systems and methods, DNA or RNA or a combination of both DNA and RNA can be processed for highly accurate HLA prediction and can be derived from tumor or blood DNA or RNA. In a further aspect, suitable methods and considerations for high accuracy computerized HLA typing are described in International PCT/US16/48768, which is incorporated herein by reference.

Where desired, neoepitopes can be scored/ranked according to allele frequency multiplied by number per million transcripts to obtain a likelihood score. The HLA information can then be used to further augment this score and calculate the actual binding affinity to the patient's HLA type. For example, an exemplary sort format could be:

>254 NM_001000.3 RPL39 Missense p.M29K A->T Normal:WIRMKTGNK,AF:0.179104477612 TPM:1023.96

TPM_MEDIAN:7.35 LL:183.395820896 netMHC:242.96 Allele:HLA-A0301WIRKKTGNK.

Here, the file is a FASTA format file, and entries start with a ">" character, which simply reports sample information. The following lines are the new epitopes. In this sample info line contains the number used to index the sample (e.g. 254), Refseq Gene ID (e.g. NM_001000.3), HUGO common name (e.g. RPL39), variant classification (e.g. missense), protein alteration (e.g. p.M29K), base pair change (e.g. A->T), normal epitope (e.g. normal: WIRMKTGNK), allele frequency (e.g. AF: 0.179104477612), transcripts per million for this gene (e.g. TPM: 1023.96), TPM_MEDIAN which is the median expression level of all the genes (eg TPM_MEDIAN: 7.35), LL score which is AF x TPM (eg LL: 183.395820896), netMHC predicted binding value (eg netMHC: 242.96) and the new The specific HLA allele to which the epitope binds (eg allele: HLA-A0301). Then, the next row is a neo-epitope (eg WIRKKTGNK).

Once patient- and tumor-specific neo-epitopes and HLA types are identified, the optimal binder (e.g., lowest KD, e.g., less than 500 nM, or less than 250 nM, or less than 150 nM or less than 50 nM) can be determined by docking the neo-epitopes to HLA , for example using NetMHC, for further computational analysis. It will be appreciated that this approach will identify not only specific neo-epitopes that are true for the patient and tumor, but also those that are most likely to be presented on cells and thus most likely to elicit a therapeutically effective immune response. bit. Of course, it should also be understood that, as discussed further below, the HLA-matched neo-epitope so identified can be biochemically identified in vitro prior to inclusion of the nucleic acid encoding the epitope as payload in the virus.

Of course, it should be understood that matching a patient's HLA type to patient-specific and cancer-specific neoepitopes can be accomplished using systems other than NetMHC, and suitable systems include NetMHC II, NetMHCpan, the IEDB analysis resource (URL immuneepitope .org), RankPep, PREDEP, SVMHC, Epipredict, HLABinding, etc. (see eg J Immunol Methods 2011; 374:1–4). When calculating the highest affinity, care should be taken to use sequence pools of neo-epitopes in which the positions of the altered amino acids are shifted (ibid.). Alternatively or additionally, the modification of the neo-epitope may further increase the binding of the expressed neo-epitope to the patient's HLA-type by adding N- and/or C-terminal modifications. Thus, neo-epitopes can be identified native proteins or further modified to better match specific HLA types.

Also, if desired, binding to the corresponding wild-type sequence (ie, the neo-epitope sequence without amino acid changes) can be calculated to ensure high differential affinities. For example, a particularly preferred high differential affinity for MHC binding between a neoepitope and its corresponding wild-type sequence is at least 2-fold, at least 5-fold, at least 10-fold, at least 100-fold, at least 500-fold, at least 1000-fold, etc.).

Figure 2 exemplarily shows a typical result of a series of filtration steps. Here, whole-genome sequencing analysis of matched normal (i.e., compared to non-diseased tissue from the same patient) triple-negative breast cancer samples revealed relatively more ( ~18,000) of novel epitopes. Notably, the first filtering step removed more than 50% of all identified neo-epitopes based on expression intensity. Here, neo-epitope sequences expressed at levels below 20% compared to matched normal samples were removed. The remaining sequences are analyzed in silico to determine which sequences bind (eg, with less than 500 nM affinity) to a single specific HLA type from the same sample. It should be noted that again most of the neo-epitopes were eliminated and in the end less than 1.3% of all neo-epitopes were found to be suitable for use.

It should be noted that this analysis is particularly advantageous for determining HLA from DNA and/or RNA sequencing information, since each HLA type has many, often very similar alleles, and due to the traditional Alignment methods usually do not have significant discriminative power. Furthermore, it should be understood that such analysis is advantageously performed with sequencing-omics data already obtained from the patient, without the need for specialized laboratory equipment. From a different point of view, neoepitope discovery, filtering, HLA type determination of patients and even binding of the thus identified neoepitopes to specific HLA types can all be done in silico.

virus construction

Following selection of preferred patient-specific and cancer-specific HLA-matched neo-epitopes, recombinant nucleic acids can be constructed for intracellular expression and subsequent presentation of the neo-epitopes on cells. The recombinant nucleic acid comprises sequence portions encoding one or more patient- and cancer-specific neo-epitopes in an arrangement such that the neo-epitopes are involved in the MHC-I and/or MHC-II presentation pathways and MHC subtypes, known novel The epitope has a high affinity for it. This targeted and rationale-based presentation is thought to generate a more robust immune response, which can be further enhanced by subcutaneous delivery or, more typically, expression of one or more co-stimulatory molecules and/or checkpoint inhibitors. Of course, it should be understood that all means of delivering such recombinant nucleic acids are considered suitable, and that recombinant nucleic acids may be formulated as DNA vaccines, recombinant viral genomes, or DNA or RNA deliverable in transfection compositions. Therefore, it should be noted that all expression systems known in the art are considered suitable for use herein (eg, bacterial expression systems, yeast expression systems, "naked" DNA and RNA expression systems).

However, it is particularly preferred to use viruses already established in gene therapy, including adenoviruses, adeno-associated viruses, alphaviruses, herpesviruses, lentiviruses, and the like. However, adenovirus is particularly preferred, among other suitable options. Also, it is further generally preferred that the virus is replication deficient and non-immunogenic, typically by targeted deletion of selected viral proteins (eg El, E3 proteins). This desirable property can be further enhanced by deletion of E2b gene function, and high titers of recombinant virus can be achieved as recently reported using genetically modified human 293 cells (e.g. J Virol. 1998 Feb; 72(2): 926–933). Most typically, the desired nucleic acid sequence (for expression from virus-infected cells) is under the control of suitable regulatory elements well known in the art.

With regard to the integration of sequence portions encoding neo-epitopes, it should be noted that various neo-epitopes can be arranged in many ways, and that a transcriptional or translational unit can have a concatemeric arrangement of multiple epitopes, usually via short linkers. (eg, a flexible linker having 4-20 amino acids), which may further comprise a protease cleavage site. Such concatemers can include from 1 to 20 neo-epitopes (usually limited by the size of the recombinant nucleic acid that can be delivered by the virus), and it should be noted that delivery to the MHC-I and MHC-II complex The concatemers can be the same or different. Thus, and as indicated below, it will be appreciated that various peptides may be routed to specific cellular compartments, thereby achieving preferential or even specific presentation by MHC-I and/or MHC-II. Viewed from another perspective, it should be recognized that tumor-associated antigens and neoepitopes can be presented via both presentation pathways, or selectively presented to one or the other at the same time or in subsequent rounds of treatment.

With regard to the "payload" of genetically modified viruses, it is contemplated that the expression of more than one, e.g. 2, 3, 4, 5 and even more neo-epitopes is preferred, which can use a variety of differently modified viruses or viruses with more than one neo-epitope sequence (eg, tandem or chimeric sequences). Although not limiting to the present subject matter, it is generally preferred to configure the neoepitope sequence as a tandem minigene (eg aa ₁₂ -neoepitope ₁₂ -aa ₁₂ ) or as a single transcriptional unit, which may or may not be translated into a chimeric protein. Thus, it should be understood that epitopes may be presented as monomers, polymers, alone or in tandem, or as hybridized sequences with N- and/or C-terminal peptides. Most typically, nucleic acid sequences are preferably back-translated using appropriate codon usage to accommodate viral and/or host codon preferences. However, alternative codon usage or mismatched codon usage are also considered appropriate. For further suitable configurations and expression cassettes, reference is made to co-pending U.S. Provisional Applications Ser. No. 62/302168 filed March 2, 2016 and Ser. No. 62/314366 filed March 28, 2016, which Incorporated herein by reference.

It is further understood that a neoepitope sequence (eg, expressed as a single neoepitope or expressed as multiple epitopes) may be configured using appropriate sequence elements and involve one or both MHC presentation pathways. With regard to directing the thus expressed neo-epitopes to the desired MHC system, note that MHC-I presented peptides will typically be produced from the cytoplasm by proteasomal processing and delivery via the endoplasmic reticulum. Thus, expression of epitopes for MHC-I presentation will generally be directed to the cytoplasm, as further discussed in more detail below. On the other hand, peptides presented by MHC-II are typically generated from endosomal and lysosomal compartments via degradation and processing by acidic proteases (eg legumain, cathepsin L and cathepsin S) prior to delivery to the cell membrane. Thus, expression of epitopes for MHC-II presentation will generally be directed to endosomal and lysosomal compartments, as further discussed in more detail below.

In the most preferred aspect, signal peptides can be used to transport neo-epitopes to endosomal and lysosomal compartments (and direct presentation of neo-epitopes to MHC-II) or remain in the cytoplasmic space (and direct neo-epitopes to MHC-II). -1 for submission). For example, endosomal and lysosomal compartments where peptides are exported to the targeting presequence and internal targeting peptides can be used. The pre-sequence of the targeting peptide is preferably added to the N-terminus and contains 6-136 basic and hydrophobic amino acids. In the case of peroxisome targeting, the targeting sequence may be at the C-terminus. Other signals (eg signal patches) can be used and include sequence elements that are separated in the peptide sequence and become functional after proper peptide folding. Additionally, protein modifications like glycosylation can induce targeting. Among other suitable targeting signals, the inventors consider peroxisome targeting signal 1 (PTS1), C-terminal tripeptide and peroxisome targeting signal 2 (PTS2), which is located at the N-terminus nearby nonapeptides. In addition, sorting of proteins into endosomes and lysosomes can also be mediated by signals within the cytoplasmic domain of the protein, which typically comprise short linear sequences. Some signals are called tyrosine-based sorting signals and conform to NPXY or common motif. Other signals called dileucine-based signals fit the [DE]XXXL[LI] or DXXLL consensus motifs. All of these signals are recognized by peripheral protein coat components bound to the cytoplasmic surface of the membrane. Recognition by the adapter protein (AP) complexes AP-1, AP-2, AP-3 and AP-4 and [DE]XXXL[LI] signals have well-characterized specificities, while DXXLL signals are recognized by another family of adapters known as GGAs. The FYVE domain, which is involved in vacuolar protein sorting and endosomal function, can also be added. In a further aspect, endosomal compartments can also be targeted using the human CD1 tail sequence (see eg Immunology, 122, 522-531).

Trafficking to or retention in the cytoplasmic compartment may not necessarily require one or more specific sequence elements. However, at least in some aspects, an N-terminal or C-terminal cytoplasmic retention signal may be added, including a membrane-anchored protein or a membrane-anchored domain of a membrane-anchored protein. For example, membrane-anchored proteins include SNAP-25, syntaxin, synaptoprevin, synaptotagmin, vesicle-associated membrane protein (VAMP), synaptic vesicle glycoprotein (SV2), high-affinity choline transporter, neuronexin, Voltage-gated calcium channels, acetylcholinesterase, and NOTCH.

Additionally, it is contemplated that the viral delivery vehicle also encodes at least one, more typically at least two, even more typically at least three, and most typically at least four co-stimulatory molecules to enhance interaction between infected dendritic cells and T cells. Interaction. For example, suitable co-stimulatory molecules include ICAM-1 (CD54), ICOS-L and LFA-3 (CD58), especially in combination with B7.1 (CD80) and/or B7.2 (CD86). Further contemplated costimulatory molecules include 4-1BBL, CD30L, CD40, CD40L, CD48, CD70, CD112, CD155, GITRL, OX40L and TL1A. Furthermore, it will be appreciated that expression of co-stimulatory molecules will preferably be coordinated such that antigens and/or neo-epitopes are presented together with one or more co-stimulatory molecules. Therefore, co-stimulatory molecules are generally considered to be produced from a single transcript, for example using an internal ribosome entry site or 2A sequence, or from multiple transcripts.

Likewise, it is contemplated that the viral vector will further comprise portions of sequences encoding one or more peptide ligands that bind to checkpoint receptors. Most typically, binding will inhibit or at least reduce signaling through the receptor, and particularly contemplated receptors include CTLA-4 (especially for CD8+ cells) PD-1 (especially for CD4+ cells). For example, peptide conjugates may include antibody fragments and particularly scFvs, but also small molecule peptide ligands that specifically bind to the receptor. Again, it should be understood that the expression of the peptide molecules will preferably be coordinated such that the antigen and/or neo-epitope are presented together with the peptide molecule(s). Thus, the generation of peptide molecules from a single transcript, for example using an internal ribosomal entry site or 2A sequence, or from multiple transcripts is generally considered.

The viruses can then be used alone or in combination as therapeutic vaccines in pharmaceutical compositions, usually formulated as sterile ^injectable compositions with viral titers of ^104-1011 virus particles per dosage unit. Alternatively, the virus can be used to infect patient (or other HLA-matched) cells ex vivo and the cells so infected are then infused into the patient. In a further example, treatment of a patient with a virus may be accompanied by a naked form of allograft or autologous natural killer or T cells or chimeric cells expressing antibodies directed against neo-epitopes, tumor-associated antigens, or the same payload as the virus antigen receptor. Natural killer cells, including the patient-derived NK-92 cell line, can also express CD16 and can be conjugated to antibodies. As used herein, the term "administering" a pharmaceutical composition or medicament refers to both direct and indirect administration of the pharmaceutical composition or medicament, wherein direct administration of the pharmaceutical composition or medicament is typically performed by a health care professional (e.g., physician, nurse, etc.), and Wherein indirect administration includes the step of providing or making available a pharmaceutical composition or medicament for direct administration (eg, by injection, infusion, oral delivery, topical delivery, etc.) to a healthcare professional.

Finally, it should be noted that where a virus comprises a nucleic acid payload encoding multiple neo-epitopes, it is contemplated that multiple neo-epitopes may at least additively or synergistically enhance the host immune response. Similarly, where multiple viruses are used whose respective viruses have different neo-epitopes, it is contemplated that multiple neo-epitopes may at least additively or synergistically enhance the host immune response. Such additive or synergistic effects may be true for a particular tumor or stage, or specific for a particular patient parameter (eg, age, sex, previous therapy, etc.).

Testing / Quality Control

In a further contemplated approach to identifying the actual expression, processing and MHC-presentation of the neo-epitope, the inventors contemplated that the nucleic acid encoding the neo-epitope could be transfected ex vivo into patient cells or surrogate cells, and could then The thus transfected cells were analyzed for MHC presentation of epitopes. For example, it is contemplated that such patient cells include immune-potent cells of the same patient, and more preferably professional antigen-presenting cells (eg, macrophages, dendritic cells, NK cells, T cells, etc.). Alternatively, leukocytes (eg, prepared from buffy coat or otherwise) or partially enriched leukocytes may be transfected. Detection of bound neo-epitopes on the cell surface can then be performed using antibodies or synthetic conjugates as described in detail below. On the other hand, where the cells are non-patient cells, it is contemplated that the cells are HLA-matched for at least 7, or at least 8, or at least 9, or at least 10 MHC subtypes (at least up to 4 Level). Most preferably, such cells will be human (allogeneic) cells. However, other mammalian (xenogeneic) cells are also considered suitable.

In yet another contemplated aspect, verification of potential neoepitope expression may also be performed using synthetic neoepitopes, preferably labeled with an affinity marker or entity for optical detection. Such synthetic neo-epitopes can be used to detect binding of neo-epitopes to T cell receptors, MHC complexes, and the like. Furthermore, and particularly where such synthetic neo-epitopes are coupled to a solid phase, the synthetic neo-epitopes can be used to detect and isolate antibodies from patients that may already be present.

In order to obtain synthetic antibodies directed against the identified neo-epitopes, in vitro preparation of the in silico-identified neo-epitopes to generate synthetic peptides was contemplated. A variety of methods for preparing synthetic peptides are known in the art, and all known means are considered suitable for use herein. For example, peptides with cancer neoepitope sequences can be synthesized on solid phase (eg, using Merrified synthesis), by solution phase synthesis, or from smaller peptide fragments. In a less preferred aspect, peptides can also be produced by expressing recombinant nucleic acids in suitable hosts (especially where multiple neo-epitopes are on a single peptide chain, optionally with neo-epitopes or cleavage sites between in the case of a spacer).

Thus, the structure of a synthetic peptide corresponding to or comprising a neo-epitope sequence may be XL ₁ -(A _n -L ₂ ) _m -Q, where X is optional. Suitable for covalently or non-covalently linking a synthetic peptide to A coupling group or moiety for the solid phase, _L1 is an optional linker to covalently link the synthetic peptide to the solid phase or coupling group. _An is a synthetic peptide with a neoepitope sequence, where A is a natural (proteinogenic) amino acid and n is an integer from 7 to 30, and most typically an integer from 7 to 11 or 15 to 25. _L2 is an optional linker that may be present, especially when multiple synthetic peptide sequences (identical or different) are located in the construct, and m is an integer, usually 1 to 30, most typically 2 to 15. Finally, Q is an end group that can be used to couple the end of the synthetic peptide to a solid phase (e.g. to sterically confine the peptide) or to a reporter (e.g. fluorescent marker) or other functional moiety (e.g. affinity marker) . Therefore, it should be noted that when synthetic peptides are used for direct MHC-I binding, the total length will be 8 to 10 amino acids.

For example, X can be a non-covalent affinity moiety (such as biotin) that binds a corresponding binding agent (such as avidin) on a solid phase, or a chemical that reacts with the N- or C-terminal amino or carboxyl group of the peptide. group (with or without a spacer), or an selectively reactive group (such as an iodoacetyl or maleimide group) that reacts with a sulfhydryl group in the peptide or linker _L1 . _L can be used to increase the distance of the synthetic peptide from the solid phase, and thus typically comprises a flexible linear moiety (e.g., containing diol, alkoxy, glycine, etc.) ) (for example between 0.3nm and 3nm). Of course, it should also be understood that synthetic peptides can use the solid phase on which the peptides are produced and thus do not require a separate coupling group or linker.

Depending on the particular peptide synthesized and coupling method, it will be appreciated that the nature of the solid phase may vary widely, and all known solid phases for attaching peptides are considered suitable for use herein. For example, suitable solid phases include agarose beads, polymeric beads (colored or otherwise individually addressable), wall surfaces of wells in microtiter plates, paper, nitrocellulose, glass, and the like. Suitable choices of solid phase and attachment chemistry will be readily assessed by one of ordinary skill in the art. In a further preferred invention, it should also be noted that solid phases are generally suitable for use in protocols associated with phage display methods, for example to allow peptides presented on phage (or other scaffold supports) to be reversibly transformed by synthetic peptides. Bind to the solid phase. In yet another contemplated use, it should also be recognized that the solid phase may be a carrier protein for vaccination (e.g. albumin, KLH, tetanus toxoid, diphtheria toxoid, etc.) in the context of use as a vaccine or as an immunogenic compound for antibody production in a non-human mammal. Likewise, synthetic proteins can also be used as vaccines or immunogenic compounds without any carrier.

In yet another preferred method, and as discussed above, it is recognized that in the case of synthetic peptides (which comprise or correspond to cancer neo-epitopes) immobilized on a solid phase, affinity agents for neo-epitopes (and in particular are antibodies) can be isolated and/or purified. Most preferably, such isolation may involve pre-made highly diverse antibody libraries. As used herein, and unless the context indicates otherwise, the term "antibody" or "antibody" includes all isotypes and subtypes of antibodies (e.g., IgG, IgM, IgE, etc.) and all fragments thereof, including monovalent IgG, F(ab ') ₂ , Fab', Fab, scFv, scFv-Fc, VhH, etc. Furthermore, contemplated antibodies may be humanized, of human or non-human (eg rodent) origin, or may be chimeric. In a typical approach, a highly diverse library may be a phage display library with a diversity of at least ¹⁰⁹ different members, or at least ¹⁰¹⁰ different members, or even more, usually based on M13 phage and tested by pIII, pVIII, pVI or pIX display, or based on T7 phage and gene 10 capsid proteins.

It should be readily understood that the use of a large diversity library will provide several binding candidate antibodies in a relatively short period of time, which can be further selected for optimal binders. Indeed, where the binding affinity for the immobilized synthetic peptide is less than desired, it will be appreciated that the affinity can be improved by affinity maturation using protocols well known in the art. For example, low affinity ( _KD > 10 ⁻⁷ M) binders or members of smaller libraries can be affinity matured to improve binding affinity and/or kinetics using methods well known in the art (see, e.g., Briefings In Functional Genomics And Proteomics. Vol 1. No 2.189–203. July 2002). Furthermore, it should be noted that while antibody libraries are generally preferred, other scaffolds are also considered suitable and include beta barrels, ribosome display, cell surface display, etc. (see e.g. Protein Sci. 2006 Jan; 15(1 ):14-27) and in particular RNA display (eg ProcNatl Acad Sci 2001; 98(9):4825-6). Thus, it will be appreciated that, in a preferred aspect, synthetic peptides are used as baits in antibody libraries to identify high affinity binding ( _KD < 10 ⁻⁷ M, more typically _KD < 10 ⁻⁸ M) antibodies.

It will be apparent to those skilled in the art that many more modifications than those already described are possible without departing from the inventive concept herein. Accordingly, the inventive subject matter is not limited by the scope of the appended claims. Moreover, when interpreting the specification and claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms "comprises" and "comprises" should be construed as referring to elements, components or steps in a non-exclusive manner, indicating that the mentioned elements, components or steps may be present, or utilized, or in conjunction with the not expressly referenced other elements, components or steps. Where the specification claims to at least one item selected from the group consisting of A, B, C... and N, the text should be interpreted as requiring only one element from that group other than A +N or B+N etc.

Claims (as amended under Article 19 of the Treaty)

1. A method of treating cancer in a patient using immunotherapy, comprising:

producing a recombinant nucleic acid configured to express cancer-specific and patient-specific neo-epitopes;

wherein the neo-epitope is a high affinity binder of at least one MHC class I subtype or at least one MHC class II subtype of the patient's HLA class;

wherein the recombinant nucleic acid comprises a sequence element that directs presentation of the expressed neo-epitope to at least one MHC class I subtype or at least one MHC class II subtype;

transfecting a cell with the recombinant nucleic acid to thereby force the cell to express and present a cancer-specific and patient-specific neo-epitope on at least one MHC class I subtype or at least one MHC class II subtype of the cell; as well as

wherein the step of transfection is performed in the patient or wherein the transfected cells are administered to the patient.

2. The method of claim 1, wherein cancer-specific and patient-specific neo-epitopes are identified by comparing omics data of diseased and healthy tissues of the patient.

3. The method of claim 2, wherein cancer-specific and patient-specific neo-epitopes are identified by filtering by at least one of mutation type, transcriptional intensity, translational intensity, and a priori known molecular variation.

4. The method of claim 1, wherein the recombinant nucleic acid is a viral expression vector, bacterial expression vector, yeast expression vector or RNA.

5. The method of claim 1, wherein the high affinity binder has an affinity for at least one MHC class I subtype or at least one MHC class II subtype of less than 150 nM.

6. The method of claim 1, wherein the patient's HLA type is determined computerized using a de Bruijn diagram.

7. The method of claim 1, wherein the sequence element is a lysosomal targeting sequence, an endosomal targeting sequence, a peroxisome targeting sequence, or a cytoplasmic retention sequence.

8. The method of claim 1, wherein the recombinant nucleic acid further comprises at least one of a sequence encoding a costimulatory molecule and a sequence encoding a checkpoint inhibitor.

9. The method of claim 1, wherein the cells are antigen presenting cells of a patient.

10. The method of claim 1, wherein the transfection of the patient is performed using an adenovirus.

11. The method of claim 1, further comprising the step of validating presentation of neo-epitopes by at least one MHC class I subtype or by at least one MHC class II subtype in surrogate cells.

12. The method of claim 11, wherein the surrogate cells are patient cells or HLA compatible allogeneic cells previously obtained from the patient.

13. The method of claim 1, further comprising the step of validating presentation of the neo-epitope by at least one MHC class I subtype or by at least one MHC class II subtype in patient cancer cells or patient cancer tissue .

14. The method of claim 13, wherein the step of verifying presentation is performed using a synthetic conjugate or antibody that binds the neo-epitope.

15. A method of producing a recombinant nucleic acid for immunotherapy comprising:

Comparing diseased and healthy tissue omics data from patients to identify disease-associated patient-specific neoepitopes in patients;

identifying at least one MHC class I subtype and at least one MHC class II subtype of the patient's HLA type;

determining the binding affinity of the neo-epitope to at least one MHC class I subtype and at least one MHC class II subtype;

selecting the neo-epitope when the binding affinity is below a predetermined threshold;

producing a recombinant nucleic acid to include a first nucleic acid sequence encoding a costimulatory molecule and a second nucleic acid sequence encoding a selected neo-epitope, wherein the nucleic acid sequence encoding the selected neo-epitope is responsible for driving expression of the selected neo-epitope under the control of the promoter; and

wherein said nucleic acid sequence further comprises a sequence element directing the presentation of the expressed selected neo-epitope to at least one MHC class I subtype or at least one MHC class II subtype.

16. The method of claim 15, wherein the step of comparing the omics data is performed by an incremental simultaneous alignment of the omics data.

17. The method of claim 15, wherein at least one MHC class I subtype and at least one MHC class II subtype are determined in silico using a de Bruijn diagram.

18. The method of claim 15, wherein the computer determines the binding affinity of the neo-epitope to at least one MHC class I subtype and at least one MHC class II subtype, and wherein the predetermined threshold is less than 150 nM.

19. The method of claim 15, wherein the recombinant nucleic acid further comprises a third nucleic acid sequence encoding a second neoepitope.

20. The method of claim 15, wherein the recombinant nucleic acid further comprises a sequence encoding a checkpoint inhibitor.

21. The method of claim 15, wherein the sequence element is a lysosomal targeting sequence, an endosomal targeting sequence, a peroxisome targeting sequence, or a cytoplasmic retention sequence.

22. The method of claim 15, wherein the recombinant nucleic acid is an adenoviral expression vector.

23. A method of improving cancer neoantigen presentation comprising:

Comparing diseased and healthy tissue omics data from patients to identify multiple disease-associated patient-specific neoepitopes in patients;

Filtered neoepitopes are obtained by filtering disease-associated patient-specific neoepitopes by at least one of mutation type, transcriptional intensity, translational intensity, and a priori known molecular variation;

selecting from the filtered neo-epitopes high affinity binders of at least one MHC class I subtype or at least one MHC class II subtype of the patient's HLA class;

expressing the high affinity binder in patient cells or cells of a compatible HLA class, and verifying presentation of the high affinity binder by at least one MHC class I subtype or by at least one MHC class II subtype; and

Use of high affinity binders in immunotherapy formats after validation of expression.

24. The method of claim 23, wherein the step of comparing the omics data is performed by incremental simultaneous alignment of the omics data, and wherein the diseased tissue is cancerous tissue.

25. The method of claim 23, wherein the mutation type is a missense mutation, wherein the transcriptional intensity is measured by RNAseq, wherein the translational intensity is measured by selective reaction monitoring mass spectrometry, and wherein the prior known Molecular variations in the group include at least one of single nucleotide polymorphisms, short deletion and insertion polymorphisms, microsatellite markers, short tandem repeats, heterozygous sequences, polynucleotide polymorphisms, and named variants.

26. The method of claim 23, wherein the high affinity binder has an affinity for at least one MHC class I subtype or at least one MHC class II subtype of less than 150 nM.

27. The method of claim 23, wherein the patient cells or cells of a compatible HLA type are antigen presenting cells.

28. The method of claim 27, wherein the antigen presenting cells are dendritic cells, natural killer cells, macrophages or T cells.

29. The method of claim 23, wherein the cells of a compatible HLA type are of the same tissue type as the diseased tissue.

30. The method of claim 23, wherein the step of verifying the presentation of the high affinity binder uses the step of detecting the binding of the high affinity binder on the surface of patient cells or cells with compatible HLA types.

31. The method of claim 30, wherein the step of detecting binding of the high affinity binder uses a synthetic binder or an antibody that binds the high affinity binder.

32. The method of claim 23, wherein the immunotherapy modality is a recombinant adenovirus, viral expression vector, bacterial expression vector, yeast expression vector, or RNA.

33. A method of improving cancer neoantigen presentation comprising:

Comparing diseased and healthy tissue omics data from patients to identify multiple disease-associated patient-specific neoepitopes in patients;

Filtered neoepitopes are obtained by filtering disease-associated patient-specific neoepitopes by at least one of mutation type, transcriptional intensity, translational intensity, and a priori known molecular variation;

selecting from the filtered neo-epitopes high affinity binders of at least one MHC class I subtype or at least one MHC class II subtype of the patient's HLA class;

making a synthetic binder that specifically binds the high affinity binder;

detecting binding of the synthetic conjugate to cells or tissues of the patient; and

This high affinity binder was used in an immunotherapy format after validation of binding of the synthetic peptide.

34. The method of claim 33, wherein the step of comparing the omics data is performed by incremental simultaneous alignment of the omics data, and wherein the diseased tissue is cancerous tissue.

35. The method of claim 33, wherein the mutation type is a missense mutation, wherein the transcriptional intensity is measured by RNAseq, wherein the translational intensity is measured by selective reaction monitoring mass spectrometry, and wherein the previously known molecular variation comprises At least one of single nucleotide polymorphisms, short deletion and insertion polymorphisms, microsatellite markers, short tandem repeats, heterozygous sequences, polynucleotide polymorphisms, and named variants.

36. The method of claim 33, wherein the high affinity binder has an affinity for at least one MHC class I subtype or at least one MHC class II subtype of less than 150 nM.

37. The method of claim 33, wherein the synthetic conjugate is an antibody or fragment thereof, or a peptide obtained from phage display or RNA display.

38. The method of claim 33, wherein the detecting step comprises optical detection of the synthetic conjugate on cells or tissue of the patient.

39. The method of claim 38, wherein patient cells or tissue are placed in the biopsy sample.

40. The method of claim 33, wherein the immunotherapy modality is a recombinant adenovirus, viral expression vector, bacterial expression vector, yeast expression vector, or RNA.

41. A recombinant virus comprising a nucleic acid produced by the method of claim 15.

42. A pharmaceutical composition comprising the recombinant virus according to claim 41.

Claims (42)

1. A method of treating cancer in a patient using immunotherapy, comprising: producing a recombinant nucleic acid configured to express cancer-specific and patient-specific neo-epitopes; wherein the neo-epitope is a high affinity binder of at least one MHC class I subtype or at least one MHC class II subtype of the patient's HLA class; wherein the recombinant nucleic acid comprises a sequence element that directs presentation of the expressed neo-epitope to at least one MHC class I subtype or at least one MHC class II subtype; transfecting a cell with the recombinant nucleic acid to thereby force the cell to express and present a cancer-specific and patient-specific neo-epitope on at least one MHC class I subtype or at least one MHC class II subtype of the cell; as well as wherein the step of transfection is performed in the patient or wherein the transfected cells are administered to the patient. 2. The method of claim 1, wherein cancer-specific and patient-specific neo-epitopes are identified by comparing omics data of diseased and healthy tissues of the patient. 3. The method of claim 2, wherein cancer-specific and patient-specific neo-epitopes are identified by filtering by at least one of mutation type, transcriptional intensity, translational intensity, and a priori known molecular variation. 4. The method of claim 1, wherein the recombinant nucleic acid is a viral expression vector, bacterial expression vector, yeast expression vector or RNA. 5. The method of claim 1, wherein the high affinity binder has an affinity for at least one MHC class I subtype or at least one MHC class II subtype of less than 150 nM. 6. The method of claim 1, wherein the patient's HLA type is determined computerized using a de Bruijn diagram. 7. The method of claim 1, wherein the sequence element is a lysosomal targeting sequence, an endosomal targeting sequence, a peroxisome targeting sequence, or a cytoplasmic retention sequence. 8. The method of claim 1, wherein the recombinant nucleic acid further comprises at least one of a sequence encoding a costimulatory molecule and a sequence encoding a checkpoint inhibitor. 9. The method of claim 1, wherein the cells are antigen presenting cells of a patient. 10. The method of claim 1, wherein the transfection of the patient is performed using an adenovirus. 11. The method of claim 1, further comprising the step of validating presentation of neo-epitopes by at least one MHC class I subtype or by at least one MHC class II subtype in surrogate cells. 12. The method of claim 11, wherein the surrogate cells are patient cells or HLA compatible allogeneic cells previously obtained from the patient. 13. The method of claim 1, further comprising the step of validating presentation of the neo-epitope by at least one MHC class I subtype or by at least one MHC class II subtype in patient cancer cells or patient cancer tissue . 14. The method of claim 13, wherein the step of verifying presentation is performed using a synthetic conjugate or antibody that binds the neo-epitope. 15. A method of producing a recombinant nucleic acid for immunotherapy comprising: Comparing diseased and healthy tissue omics data from patients to identify disease-associated patient-specific neoepitopes in patients; identifying at least one MHC class I subtype and at least one MHC class II subtype of the patient's HLA type; determining the binding affinity of the neo-epitope to at least one MHC class I subtype and at least one MHC class II subtype; selecting the neo-epitope when the binding affinity is below a predetermined threshold; producing a recombinant nucleic acid to include a nucleic acid sequence encoding the selected neo-epitope, wherein the nucleic acid sequence encoding the selected neo-epitope is under the control of a promoter driving expression of the selected neo-epitope; and wherein said nucleic acid sequence further comprises a sequence element directing the presentation of the expressed selected neo-epitope to at least one MHC class I subtype or at least one MHC class II subtype. 16. The method of claim 15, wherein the step of comparing the omics data is performed by an incremental simultaneous alignment of the omics data. 17. The method of claim 15, wherein at least one MHC class I subtype and at least one MHC class II subtype are determined in silico using a de Bruijn diagram. 18. The method of claim 15, wherein the binding affinity of the neo-epitope to at least one MHC class I subtype and at least one MHC class II subtype is determined in silico, and wherein the predetermined threshold is less than 150 nM. 19. The method of claim 15, wherein the recombinant nucleic acid further comprises a second nucleic acid sequence encoding a second neoepitope. 20. The method of claim 15, wherein the recombinant nucleic acid further comprises at least one of a sequence encoding a co-stimulatory molecule and a sequence encoding a checkpoint inhibitor. 21. The method of claim 15, wherein the sequence element is a lysosomal targeting sequence, an endosomal targeting sequence, a peroxisome targeting sequence, or a cytoplasmic retention sequence. 22. The method of claim 15, wherein the recombinant nucleic acid is an adenoviral expression vector. 23. A method of improving cancer neoantigen presentation comprising: Comparing diseased and healthy tissue omics data from patients to identify multiple disease-associated patient-specific neoepitopes in patients; Filtered neoepitopes are obtained by filtering disease-associated patient-specific neoepitopes by at least one of mutation type, transcriptional intensity, translational intensity, and a priori known molecular variation; selecting from the filtered neo-epitopes high affinity binders of at least one MHC class I subtype or at least one MHC class II subtype of the patient's HLA class; expressing the high affinity binder in patient cells or cells of a compatible HLA class, and verifying presentation of the high affinity binder by at least one MHC class I subtype or by at least one MHC class II subtype; and Use of high affinity binders in immunotherapy formats after validation of expression. 24. The method of claim 23, wherein the step of comparing the omics data is performed by incremental simultaneous alignment of the omics data, and wherein the diseased tissue is cancerous tissue. 25. The method of claim 23, wherein the mutation type is a missense mutation, wherein the transcriptional intensity is measured by RNAseq, wherein the translational intensity is measured by selective reaction monitoring mass spectrometry, and wherein the prior known Molecular variations in the group include at least one of single nucleotide polymorphisms, short deletion and insertion polymorphisms, microsatellite markers, short tandem repeats, heterozygous sequences, polynucleotide polymorphisms, and named variants. 26. The method of claim 23, wherein the high affinity binder has an affinity for at least one MHC class I subtype or at least one MHC class II subtype of less than 150 nM. 27. The method of claim 23, wherein the patient cells or cells of a compatible HLA type are antigen presenting cells. 28. The method of claim 27, wherein the antigen presenting cells are dendritic cells, natural killer cells, macrophages or T cells. 29. The method of claim 23, wherein the cells of a compatible HLA type are of the same tissue type as the diseased tissue. 30. The method of claim 23, wherein the step of verifying the presentation of the high affinity binder uses the step of detecting the binding of the high affinity binder on the surface of patient cells or cells with compatible HLA types. 31. The method of claim 30, wherein the step of detecting binding of the high affinity binder uses a synthetic binder or an antibody that binds the high affinity binder. 32. The method of claim 23, wherein the immunotherapy modality is a recombinant adenovirus, viral expression vector, bacterial expression vector, yeast expression vector, or RNA. 33. A method of improving cancer neoantigen presentation comprising: Comparing diseased and healthy tissue omics data from patients to identify multiple disease-associated patient-specific neoepitopes in patients; Filtered neoepitopes are obtained by filtering disease-associated patient-specific neoepitopes by at least one of mutation type, transcriptional intensity, translational intensity, and a priori known molecular variation; selecting from the filtered neo-epitopes high affinity binders of at least one MHC class I subtype or at least one MHC class II subtype of the patient's HLA class; making a synthetic binder that specifically binds the high affinity binder; detecting binding of the synthetic conjugate to cells or tissues of the patient; and This high affinity binder was used in an immunotherapy format after validation of binding of the synthetic peptide. 34. The method of claim 33, wherein the step of comparing the omics data is performed by incremental simultaneous alignment of the omics data, and wherein the diseased tissue is cancerous tissue. 35. The method of claim 33, wherein the mutation type is a missense mutation, wherein the transcriptional intensity is measured by RNAseq, wherein the translational intensity is measured by selective reaction monitoring mass spectrometry, and wherein the previously known molecular variation comprises At least one of single nucleotide polymorphisms, short deletion and insertion polymorphisms, microsatellite markers, short tandem repeats, heterozygous sequences, polynucleotide polymorphisms, and named variants. 36. The method of claim 33, wherein the high affinity binder has an affinity for at least one MHC class I subtype or at least one MHC class II subtype of less than 150 nM. 37. The method of claim 33, wherein the synthetic conjugate is an antibody or fragment thereof, or a peptide obtained from phage display or RNA display. 38. The method of claim 33, wherein the detecting step comprises optical detection of synthetic conjugates on cells or tissues of the patient. 39. The method of claim 38, wherein patient cells or tissue are placed in the biopsy sample. 40. The method of claim 33, wherein the immunotherapy modality is a recombinant adenovirus, viral expression vector, bacterial expression vector, yeast expression vector, or RNA. 41. A recombinant virus comprising a nucleic acid produced by the method of claim 15. 42. A pharmaceutical composition comprising the recombinant virus according to claim 41.